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Parallel MATLAB for Multicore and Multinode Computers

Parallel MATLAB for Multicore and Multinode Computers


Part of Software, Environments and Tools

  • Date Published: July 2009
  • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • format: Hardback
  • isbn: 9780898716733

£ 52.00

This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
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About the Authors
  • This is the first book on parallel MATLAB and the first parallel computing book focused on the design, code, debug, and test techniques required to quickly produce efficient parallel programs. MATLAB is currently the dominant language of technical computing with one million users worldwide, many of whom can benefit from the increased power offered by inexpensive multicore and multinode parallel computers. MATLAB is an ideal environment for learning about parallel computing, allowing the user to focus on parallel algorithms instead of the details of implementation. This book is a reference for professional scientists and engineers and will also be beneficial to graduate students and advanced undergraduate students as a textbook for a parallel computing course.

    • This book covers more parallel algorithms and parallel programming models than any other parallel programming book due to the succinctness of MATLAB
    • Promotes a 'hands on' approach with numerous examples
    • Examples are drawn from widely known and well-documented parallel benchmark codes that are representative of many real applications across the field of technical computing
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    Product details

    • Date Published: July 2009
    • format: Hardback
    • isbn: 9780898716733
    • dimensions: 261 x 182 x 21 mm
    • weight: 0.68kg
    • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • Table of Contents

    List of figures
    List of tables
    List of algorithms
    Part I. Fundamentals:
    1. Primer: notation and interfaces
    2. Introduction to pMATLAB
    3. Interacting with distributed arrays
    Part II. Advanced Techniques:
    4. Parallel programming models
    5. Advanced distributed array programming
    6. Performance metrics and software architecture
    Part III. Case Studies:
    7. Parallel application analysis
    8. Stream
    9. RandomAccess
    10. Fast Fourier transform
    11. High performance Linpack
    Appendix. Notation for hierarchical parallel multicore algorithms

  • Author

    Jeremy Kepner, Massachusetts Institute of Technology
    Jeremy Kepner is a senior technical staff member at MIT Lincoln Laboratory. His research focuses on the development of advanced libraries for the application of massively parallel computing to a variety of data intensive signal processing problems on which he has published many articles. Jeremy is most proud of the opportunity he has had to be the principal architect, principal investigator, or otherwise co-leader of several very talented teams. These teams have produced a number of innovative technologies that have broken new ground in parallel computing.

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